scholarly journals Coupling Grammar and Knowledge Base: Range Concatenation Grammars and Description Logics

2004 ◽  
pp. 195-202 ◽  
Author(s):  
Benoît Sagot ◽  
Adil El Ghali
Keyword(s):  
Knowledge Base ◽  
Description Logics ◽  
Base Range

scholarly journals Extensible Knowledge Representation: the Case of Description Reasoners

1999 ◽  
Vol 10 ◽  
pp. 399-434 ◽  
Author(s):  
A. Borgida
Keyword(s):  
Knowledge Representation ◽  
Knowledge Base ◽  
Software Architecture ◽  
Description Logics ◽  
Knowledge Representation And Reasoning ◽  
Heuristic Methodology

This paper offers an approach to extensible knowledge representation and reasoning for a family of formalisms known as Description Logics. The approach is based on the notion of adding new concept constructors, and includes a heuristic methodology for specifying the desired extensions, as well as a modularized software architecture that supports implementing extensions. The architecture detailed here falls in the normalize-compared paradigm, and supports both intentional reasoning (subsumption) involving concepts, and extensional reasoning involving individuals after incremental updates to the knowledge base. The resulting approach can be used to extend the reasoner with specialized notions that are motivated by specific problems or application areas, such as reasoning about dates, plans, etc. In addition, it provides an opportunity to implement constructors that are not currently yet sufficiently well understood theoretically, but are needed in practice. Also, for constructors that are provably hard to reason with (e.g., ones whose presence would lead to undecidability), it allows the implementation of incomplete reasoners where the incompleteness is tailored to be acceptable for the application at hand.

scholarly journals Reasoning About Typicality and Probabilities in Preferential Description Logics

2020 ◽  
Author(s):  
Laura Giordano ◽  
Valentina Gliozzi ◽  
Antonio Lieto ◽  
Nicola Olivetti ◽  
Gian Luca Pozzato
Keyword(s):  
Knowledge Base ◽  
Minimal Model ◽  
Description Logics ◽  
The Other ◽  
Rational Closure ◽  
Preferential Semantics ◽  
Concept Combination ◽  
Basic Concepts ◽  
The One ◽  
Property Inheritance

In this work we describe preferential Description Logics of typicality, a nonmonotonic extension of standard Description Logics by means of a typicality operator T allowing to extend a knowledge base with inclusions of the form T(C) ⊑ D, whose intuitive meaning is that “normally/typically Cs are also Ds”. This extension is based on a minimal model semantics corresponding to a notion of rational closure, built upon preferential models. We recall the basic concepts underlying preferential Description Logics. We also present two extensions of the preferential semantics: on the one hand, we consider probabilistic extensions, based on a distributed semantics that is suitable for tackling the problem of commonsense concept combination, on the other hand, we consider other strengthening of the rational closure semantics and construction to avoid the so called “blocking of property inheritance problem”.

scholarly journals A Framework for Reasoning about Dynamic Axioms in Description Logics

2020 ◽  
Author(s):  
Bartosz Bednarczyk ◽  
Stephane Demri ◽  
Alessio Mansutti
Keyword(s):  
Knowledge Representation ◽  
Knowledge Base ◽  
Data Structures ◽  
Description Logics ◽  
Knowledge Bases ◽  
Dynamic Data Structures ◽  
Dynamic Data ◽  
Logical Connectives ◽  
Consistency Problem ◽  
Natural Means

Description logics are well-known logical formalisms for knowledge representation. We propose to enrich knowledge bases (KBs) with dynamic axioms that specify how the satisfaction of statements from the KBs evolves when the interpretation is decomposed or recomposed, providing a natural means to predict the evolution of interpretations. Our dynamic axioms borrow logical connectives from separation logics, well-known specification languages to verify programs with dynamic data structures. In the paper, we focus on ALC and EL augmented with dynamic axioms, or to their subclass of positive dynamic axioms. The knowledge base consistency problem in the presence of dynamic axioms is investigated, leading to interesting complexity results, among which the problem for EL with positive dynamic axioms is tractable, whereas EL with dynamic axioms is undecidable.

Research on Consistency Checking of OntoUML Model

2012 ◽  
Vol 433-440 ◽  
pp. 2862-2867
Author(s):  
Bin Yang ◽  
Yu Dong Qi ◽  
Xiu We Wang ◽  
Ya Ning Wang
Keyword(s):  
Knowledge Base ◽  
Conceptual Model ◽  
Description Logics ◽  
Conceptual Modeling ◽  
Modeling Language ◽  
Consistency Checking ◽  
Model Based ◽  
Reasoning System ◽  
Uml Metamodel

OntoUML is a conceptual modeling language which is built with a lightweight expansion of UML metamodel, but it doesn’t provide mechanism of consistency checking on conceptual model. The correctness of the syntax and semantics of the model still need artificial check. The paper introduced OntoUML briefly and put forward a scheme of consistency checking of OntoUML model based on description logics. By transforming into knowledge base of description logics, the detection of consistencies at the OntoUML model can be realized using existing mature reasoning system.

scholarly journals Reasoning with Very Expressive Fuzzy Description Logics

2007 ◽  
Vol 30 ◽  
pp. 273-320 ◽  
Author(s):  
G. Stoilos ◽  
G. Stamou ◽  
J. Z. Pan ◽  
V. Tzouvaras ◽  
I. Horrocks
Keyword(s):  
Knowledge Representation ◽  
Knowledge Base ◽  
High Performance ◽  
Description Logics ◽  
Decision Procedures ◽  
Satisfiability Problem ◽  
Fuzzy Description Logics ◽  
Knowledge Based ◽  
Fuzzy Description

It is widely recognized today that the management of imprecision and vagueness will yield more intelligent and realistic knowledge-based applications. Description Logics (DLs) are a family of knowledge representation languages that have gained considerable attention the last decade, mainly due to their decidability and the existence of empirically high performance of reasoning algorithms. In this paper, we extend the well known fuzzy ALC DL to the fuzzy SHIN DL, which extends the fuzzy ALC DL with transitive role axioms (S), inverse roles (I), role hierarchies (H) and number restrictions (N). We illustrate why transitive role axioms are difficult to handle in the presence of fuzzy interpretations and how to handle them properly. Then we extend these results by adding role hierarchies and finally number restrictions. The main contributions of the paper are the decidability proof of the fuzzy DL languages fuzzy-SI and fuzzy-SHIN, as well as decision procedures for the knowledge base satisfiability problem of the fuzzy-SI and fuzzy-SHIN.

scholarly journals SEMANTIC IMAGE ANALYSIS USING A SYMBOLIC NEURAL ARCHITECTURE

2010 ◽  
Vol 29 (3) ◽  
pp. 159 ◽  
Author(s):  
Ilianna Kollia ◽  
Nikolaos Simou ◽  
Andreas Stafylopatis ◽  
Stefanos Kollias
Keyword(s):  
Image Analysis ◽  
Knowledge Base ◽  
Description Logics ◽  
A Priori ◽  
Machine Learning Techniques ◽  
Video Frames ◽  
Multimedia Search ◽  
Neural Network Classifiers ◽  
Classification Of Images ◽  
Semantic Image Analysis

Image segmentation and classification are basic operations in image analysis and multimedia search which have gained great attention over the last few years due to the large increase of digital multimedia content. A recent trend in image analysis aims at incorporating symbolic knowledge representation systems and machine learning techniques. In this paper, we examine interweaving of neural network classifiers and fuzzy description logics for the adaptation of a knowledge base for semantic image analysis. The proposed approach includes a formal knowledge component, which, assisted by a reasoning engine, generates the a-priori knowledge for the image analysis problem. This knowledge is transferred to a kernel based connectionist system, which is then adapted to a specific application field through extraction and use of MPEG-7 image descriptors. Adaptation of the knowledge base can be achieved next. Combined segmentation and classification of images, or video frames, of summer holidays, is the field used to illustrate the good performance of the proposed approach.

scholarly journals Acquiring Ontology Axioms through Mappings to Data Sources

2019 ◽  
Vol 11 (12) ◽  
pp. 260
Author(s):  
Floriana Di Pinto ◽  
Giuseppe De Giacomo ◽  
Domenico Lembo ◽  
Maurizio Lenzerini ◽  
Riccardo Rosati
Keyword(s):  
Knowledge Base ◽  
Description Logic ◽  
Description Logics ◽  
Data Access ◽  
Data Sources ◽  
New Concepts ◽  
Source Data ◽  
Meta Modeling ◽  
Definition Of ◽  
Do So

Although current languages used in ontology-based data access (OBDA) systems allow for mapping source data to instances of concepts and relations in the ontology, several application domains need more flexible tools for inferring knowledge from data, which are able to dynamically acquire axioms about new concepts and relations directly from the data. In this paper we introduce the notion of mapping-based knowledge base (MKB) to formalize the situation where both the extensional and the intensional level of the ontology are determined by suitable mappings to a set of data sources. This allows for making the intensional level of the ontology as dynamic as the extensional level traditionally is. To do so, we resort to the meta-modeling capabilities of higher-order description logics, in particular the description logic Hi ( DL-Lite R ) , which allows seeing concepts and relations as individuals, and vice versa. The challenge in this setting is to design efficient algorithms for answering queries posed to MKBs. Besides the definition of MKBs, our main contribution is to prove that answering instance queries posed to MKBs expressed in Hi ( DL-Lite R ) can be done efficiently.

scholarly journals Incoherency Problems in a Combination of Description Logics and Rules

2014 ◽  
Vol 2014 ◽  
pp. 1-6 ◽  
Author(s):  
Shasha Huang ◽  
Jing Hao ◽  
Dang Luo
Keyword(s):  
Knowledge Base ◽  
Description Logics ◽  
Knowledge Bases ◽  
Combination Method ◽  
Trust Level ◽  
Level Information ◽  
The Relationship

A paraconsistent semantics has been presented for hybrid MKNF knowledge bases—a combination method for description logics and rules. However, it is invalid when incoherency occurs in the knowledge base. In this paper, we introduce a semi-S5semantics for hybrid MKNF knowledge bases on the basis of nine-valued lattice, such that it is paraconsistent for incoherent knowledge base. It is shown that a semi-S5model can be computed via a fixpoint operator and is in fact a paraconsistent MKNF model when the knowledge base is incoherent. Moreover, we apply six-valued lattice to hybrid MKNF knowledge bases and present a suspicious semantics to distinguish different trust level information. At last, we investigate the relationship between suspicious semantics and paraconsistent semantics.

scholarly journals The role of semantics in mining frequent patterns from knowledge bases in description logics with rules

2010 ◽  
Vol 10 (3) ◽  
pp. 251-289 ◽  
Author(s):  
JOANNA JÓZEFOWSKA ◽  
AGNIESZKA ŁAWRYNOWICZ ◽  
TOMASZ ŁUKASZEWSKI
Keyword(s):  
Data Mining ◽  
Semantic Web ◽  
Knowledge Base ◽  
Description Logics ◽  
Pattern Discovery ◽  
Knowledge Bases ◽  
Frequent Pattern ◽  
Frequent Patterns ◽  
Representation Formalism

AbstractWe propose a new method for mining frequent patterns in a language that combines both Semantic Web ontologies and rules. In particular, we consider the setting of using a language that combines description logics (DLs) with DL-safe rules. This setting is important for the practical application of data mining to the Semantic Web. We focus on the relation of the semantics of the representation formalism to the task of frequent pattern discovery, and for the core of our method, we propose an algorithm that exploits the semantics of the combined knowledge base. We have developed a proof-of-concept data mining implementation of this. Using this we have empirically shown that using the combined knowledge base to perform semantic tests can make data mining faster by pruning useless candidate patterns before their evaluation. We have also shown that the quality of the set of patterns produced may be improved: the patterns are more compact, and there are fewer patterns. We conclude that exploiting the semantics of a chosen representation formalism is key to the design and application of (onto-)relational frequent pattern discovery methods.

Sign in / Sign up

Export Citation Format

Share Document